Abstract
With the rapid development of land marketization in China, the spatial patterns of residential land prices in different regions have become increasingly complicated. The very high and continuously rising residential land prices in many cities are causing significant challenges to economic development and social stability. Yet, there has only been a limited amount of attempts made to model and analyze the regional dynamic changes of residential land price systematically, especially in term of the spatially varying effects of key demographic and economic factors. In this study we provided a perspective analysis of the changes of residential land prices in 2008, 2011 and 2014 based on the land price monitoring records of 105 cities and then conducted a geographically weighted regression (GWR) analysis on the relationships between residential land price and three major impact factors (i.e., immigrant population, gross domestic product (GDP) and investment in residential buildings). Results show that the areas in which GDP had relatively strong positive impacts on residential land price expanded with time. The negative effects of immigrant population on residential land price were mainly concentrated in the cities around the Bohai Rim and the area with negative effects gradually shrank in the three studied years. Conversely, the areas with negative correlation between investment in residential buildings and residential land price gradually expanded in size over time. A geographical detector was used to examine the relative importance of factors to residential land price. It was found that the GDP had more significant influence on residential land price than other factors and the influence of the three factors to overall variation in residential land price increased over the three studied years. These results underscore the importance of taking spatially varying effects of major driving factors into account in policy-making on regional land market.
Highlights
In the past three decades, unprecedented urbanization occurred in China and this phenomenon has attracted the attention of many researchers [1,2,3,4]
The geographically weighted regression (GWR) method was usually compared with global spatial statistical methods, such as the ordinary least squares (OLS) regression, regression kriging, or co-kriging and the comparisons showed the advantages of GWR in improving mapping quality and exploring spatially varying local relationships [47,48,49,50,51]
This study intends to obtain a better understanding of the spatial variation of urban residential land prices caused by long-term marketization and major impact factors in China, using a local spatial statistical method–GWR and a geographical detector
Summary
In the past three decades, unprecedented urbanization occurred in China and this phenomenon has attracted the attention of many researchers [1,2,3,4]. China’s urban population changed from 17.9% of the total population in 1978 to 54.8% in 2014. This notable global event may be the greatest human-resettlement experiment in human history [5]. The Chinese government has kept tightening land supply on primary land markets. Because of these aforementioned reasons, exceptional purchasing booms, especially in big cities, have appeared in China’s real estate market. Chinese urban dwellers currently live under heavy pressure due to the high house prices and the forthcoming unpredictability of changes in the real estate market [12,13]
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